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Instance st_e11

Formats ams gms mod nl osil py
Primal Bounds (infeas ≤ 1e-08)
189.31162970 p1 ( gdx sol )
(infeas: 0)
Other points (infeas > 1e-08)  
Dual Bounds
189.31162950 (ANTIGONE)
189.31162950 (BARON)
189.31162970 (COUENNE)
189.31162970 (LINDO)
189.31162970 (SCIP)
References Tawarmalani, M and Sahinidis, N V, Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications, Kluwer, 2002.
Westerberg, A W and Shah, J V, Assuring a global optimum by the use of an upper bound on the lower (dual) bound, Computers and Chemical Engineering, 2:2-3, 1978, 83-92.
Source BARON book instance misc/e11
Added to library 03 Sep 2002
Problem type NLP
#Variables 3
#Binary Variables 0
#Integer Variables 0
#Nonlinear Variables 3
#Nonlinear Binary Variables 0
#Nonlinear Integer Variables 0
Objective Sense min
Objective type signomial
Objective curvature concave
#Nonzeros in Objective 2
#Nonlinear Nonzeros in Objective 2
#Constraints 2
#Linear Constraints 1
#Quadratic Constraints 1
#Polynomial Constraints 0
#Signomial Constraints 0
#General Nonlinear Constraints 0
Operands in Gen. Nonlin. Functions  
Constraints curvature indefinite
#Nonzeros in Jacobian 4
#Nonlinear Nonzeros in Jacobian 2
#Nonzeros in (Upper-Left) Hessian of Lagrangian 4
#Nonzeros in Diagonal of Hessian of Lagrangian 2
#Blocks in Hessian of Lagrangian 2
Minimal blocksize in Hessian of Lagrangian 1
Maximal blocksize in Hessian of Lagrangian 2
Average blocksize in Hessian of Lagrangian 1.5
#Semicontinuities 0
#Nonlinear Semicontinuities 0
#SOS type 1 0
#SOS type 2 0
Minimal coefficient 6.0000e-01
Maximal coefficient 6.0000e+02
Infeasibility of initial point 1.5e+04
Sparsity Jacobian Sparsity of Objective Gradient and Jacobian
Sparsity Hessian of Lagrangian Sparsity of Hessian of Lagrangian

$offlisting
*  
*  Equation counts
*      Total        E        G        L        N        X        C        B
*          3        3        0        0        0        0        0        0
*  
*  Variable counts
*                   x        b        i      s1s      s2s       sc       si
*      Total     cont   binary  integer     sos1     sos2    scont     sint
*          4        4        0        0        0        0        0        0
*  FX      0
*  
*  Nonzero counts
*      Total    const       NL      DLL
*          7        3        4        0
*
*  Solve m using NLP minimizing objvar;


Variables  x1,x2,x3,objvar;

Positive Variables  x1,x2,x3;

Equations  e1,e2,e3;


e1.. 600*x1 - x1*x3 - 50*x3 =E= -5000;

e2..    600*x2 + 50*x3 =E= 15000;

e3.. -(35*x1**0.6 + 35*x2**0.6) + objvar =E= 0;

* set non-default bounds
x1.up = 34;
x2.up = 17;
x3.up = 300;

Model m / all /;

m.limrow=0; m.limcol=0;
m.tolproj=0.0;

$if NOT '%gams.u1%' == '' $include '%gams.u1%'

$if not set NLP $set NLP NLP
Solve m using %NLP% minimizing objvar;


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